Predictors of RNs' intent to work and work decisions 1 year later in a U.S. national sample

Abstract

Background: Many studies have examined predictors of nurses' intention to work in their job, including desire to quit. Intent has been a good predictor of actual turnover. Few longitudinal studies exist that consider regional variables.

Objectives: To extend the conceptual framework of turnover research to the whole nursing workforce and determine: (1) how do demographics, region (metropolitan statistical area: MSA), movement opportunities, and work setting variables affect registered nurses' (RNs) intent to work and desire to quit; and (2) how do demographics, MSA variables, movement opportunities, and work setting variables affect RNs' work behavior at time 2?

Design: Panel study using Dillman's design method.

Settings and participants: Randomly selected national cluster sample from 40 urban geographic regions (MSAs) in 29 states of the United States.

Methods: Four thousand surveys were sent. There were 1907 female RNs under 65 (48% response rate) from year 1 of which 1348 responded at year 2 (70% response rate).

Results: The first analyses used desire to quit (explained 65% of the variance) and intent to work from year 1 as dependent variables. Satisfaction and organizational commitment were significant negative predictors of desire to quit. In the logistic regression on intent to work, the work motivation and work-family conflict were positive and significant as well as wages (negative) and three benefit variables. In year 2, the dependent variable was working or not and if working, full-time or not. For this bivariate probit regression no attitudes influenced the work/not work decision, but MSA level variables, wages (positive) and benefits (positive) did. Organizational commitment and higher workload increased the probability of working FT.

Conclusions: Regional differences across markets need to be controlled and their influence investigated. In addition, attitudes as well as wages and benefits were important in certain decisions: these factors are clearly under the influence of employers.